Suggested Citation:"Appendix B: Questions on Directions and Needs for Advanced Cyberinfrastructure." National Research Council. 2014. Future Directions for NSF Advanced Computing Infrastructure to Support U.S. Science and Engineering in 2017-2020: Interim Report. Washington, DC: The National Academies Press. doi: 10.17226/18972.

The committee seeks input from the community on the directions and needs for cyber infrastructure and provides a list of key issues in the body of the report. This appendix contains additional issues and questions on which the committee will be asking input. The committee seeks both responses to these questions and suggestions for other issues on which to request input.

GENERAL ISSUES

• The trajectory and relevance of large-scale simulation’s impact on foundational advances in science and engineering.

• Scientific research grand challenges that will be substantially advanced by large-scale data analytics and data mining not currently possible in research infrastructures.

• Areas for research about cyberinfrastructure investments (e.g., emergent technologies and algorithms, balance between experimental and “production” systems, education and workforce development, community software) required to support sustained advances in U.S. science.

• Challenges and responses by research infrastructures at all scales (e.g., campus, regional, national; problem-focused or multipurpose) to the items above, identifying those that can be most positively affected by the National Science Foundation (NSF). These should encompass economic, cross-agency, and international considerations.

Suggested Citation:"Appendix B: Questions on Directions and Needs for Advanced Cyberinfrastructure." National Research Council. 2014. Future Directions for NSF Advanced Computing Infrastructure to Support U.S. Science and Engineering in 2017-2020: Interim Report. Washington, DC: The National Academies Press. doi: 10.17226/18972.

a. What are some of the open problems in your field that require large-scale simulation to solve? Which might lead to fundamental or foundational advances? Why are these problems not being solved today?

b. What are some of the open problems in your field that require data-intensive computing, such as large-scale data analytics and data mining? Why are these problems not being solved today?

c. Are there plans or roadmaps that characterize future computing needs in your field?

d. What types of new workflows are emerging that require complex access pathways between data sets, computation, and storage?

2. Advanced computing capabilities, facilities, requirements

e. What forms of computing are used in your field? For example, How does your field make use of laptop/desktops, research group clusters, department or campus commodity cluster systems, mid- to large-scale, shared capacity systems such as XSEDE, leadership-class capability systems such as Blue Waters (NSF) or Mira (Department of Energy), or commercial cloud services such as Amazon EC2? How would you characterize the importance of access to each type—required, desirable, or unnecessary? How might these needs change in the future, and why?

f. How are data sets evolving in terms of variety and distribution? Do you access tens to hundreds of near-real-time data sets? Do you rely on a few large repositories?

g. With computer hardware and software evolving more rapidly than in the recent past, what impacts do you see for your field? For example, what role will new hardware such as accelerators (GPUs or Intel Xeon Phi), FPGAs, new memory systems, or new I/O systems play? Are there barriers to their adoption, such as challenges making necessary modifications to software?

h. What software does your field depend on? Who develops and maintains this code, and how is this work supported?

i. Is your field keeping up the technical skills needed to use new technical capabilities?

3. Challenges and suggestions

j. What are the biggest challenges that your field faces in using computation? Consider access to systems with sufficient capability and capacity; productivity of environments; algorithms; workforce; stability of software and hardware; and the ability to use systems efficiently, including parallelism and scalability.

Suggested Citation:"Appendix B: Questions on Directions and Needs for Advanced Cyberinfrastructure." National Research Council. 2014. Future Directions for NSF Advanced Computing Infrastructure to Support U.S. Science and Engineering in 2017-2020: Interim Report. Washington, DC: The National Academies Press. doi: 10.17226/18972.

k. What investments would have the greatest positive impact on your research field? For example, this could be more computer systems to increase access, different kinds of systems with a different balance of capability, support for community software, development of new algorithms, or a workforce with better training in computational science.

l. What other elements of national cyber infrastructure would significantly advance the pace of discovery or expand participation? Examples might include shared file systems or standard services and application program interfaces.

Suggested Citation:"Appendix B: Questions on Directions and Needs for Advanced Cyberinfrastructure." National Research Council. 2014. Future Directions for NSF Advanced Computing Infrastructure to Support U.S. Science and Engineering in 2017-2020: Interim Report. Washington, DC: The National Academies Press. doi: 10.17226/18972.

Suggested Citation:"Appendix B: Questions on Directions and Needs for Advanced Cyberinfrastructure." National Research Council. 2014. Future Directions for NSF Advanced Computing Infrastructure to Support U.S. Science and Engineering in 2017-2020: Interim Report. Washington, DC: The National Academies Press. doi: 10.17226/18972.

Suggested Citation:"Appendix B: Questions on Directions and Needs for Advanced Cyberinfrastructure." National Research Council. 2014. Future Directions for NSF Advanced Computing Infrastructure to Support U.S. Science and Engineering in 2017-2020: Interim Report. Washington, DC: The National Academies Press. doi: 10.17226/18972.

Advanced computing capabilities are used to tackle a rapidly growing range of challenging science and engineering problems, many of which are compute- and data-intensive as well. Demand for advanced computing has been growing for all types and capabilities of systems, from large numbers of single commodity nodes to jobs requiring thousands of cores; for systems with fast interconnects; for systems with excellent data handling and management; and for an increasingly diverse set of applications that includes data analytics as well as modeling and simulation. Since the advent of its supercomputing centers, the National Science Foundation (NSF) has provided its researchers with state-of-the-art computing systems. The growth of new models of computing, including cloud computing and publically available by privately held data repositories, opens up new possibilities for NSF. In order to better understand the expanding and diverse requirements of the science and engineering community and the importance of a new broader range of advanced computing infrastructure, the NSF requested that the National Research Council carry out a study examining anticipated priorities and associated tradeoffs for advanced computing. This interim report identifies key issues and discusses potential options.

Future Directions for NSF Advanced Computing Infrastructure to Support U.S. Science and Engineering in 2017-2020 examines priorities and associated tradeoffs for advanced computing in support of NSF-sponsored science and engineering research. This report is an initial compilation of issues to be considered as future NSF strategy, budgets, and programs for advanced computing are developed. Included in the report are questions on which the authoring committee invites comment. We invite your feedback on this report, and more generally, your comments on the future of advanced computing at NSF.

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